Hydrocarbon fluids such as oil and natural gas are obtained from a subterranean geologic formation, referred to as a reservoir, by drilling a well that penetrates the hydrocarbon-bearing formation. Once a wellbore is drilled, various forms of well completion components may be installed in order to control and enhance the efficiency of producing the various fluids from the reservoir. Information from the wells can prove valuable, but reliably obtaining useful information from the well is difficult.
Distributed vibration sensing (DVS, also known as distributed acoustic sensing DAS) is used increasingly to measure seismic signals in wells and also to detect noise relating to flow events, as examples. These techniques are based on optical time domain reflectometry in which one or more pulse(s) of probe light are (is) launched into the fibre. The signal consists of light that is scattered by fixed inhomogeneities in the glass and then re-captured by the waveguide in the return direction. With a coherent source illumination, the scattering from all the scatterers is re-remitted with a fixed phase, resulting in a speckle-like signal that is highly sensitive to the source frequency and the precise disposition of the scatterers. If the fibre is undisturbed and the source frequency is stable, then so too is the amplitude and the phase of the scattered electric field. However, if the fibre is strained by a small fraction of an optical wavelength, then the backscatter signal is altered. The sensitivity of the measurement is of the order of nanometers or in some cases of order 1-200 pm.
In heterodyne DVS and some other techniques, the phase of the light scattered by two locations separated by a distance known as the gauge length (GL) is compared. This provides a more linear response to strain than measuring the backscatter intensity. A review of some of the different techniques for acquiring this type of data is given in a paper by A. H. Hartog, L. B. Liokumovich, and O. I. Kotov entitled “The Optics of Distributed Vibration Sensing,” published in 2013.